Title :
Large-scale distributed storage for highly concurrent Mapreduce applications
Author :
Moise, Diana ; Antoniu, Advisor Gabriel ; Bougé, Advisor Luc
Author_Institution :
INRIA, IRISA, Rennes, France
Abstract :
A large part of today´s most popular applications are data-intensive. Whether they are scientific applications or Internet services, the data volume they process is continuously growing. Two main aspects arise when trying to accomodate the size of the data: processing the computation in a manner that is efficient both in terms of resources and time, and providing storage capable to deal with the requirements of data-intensive applications. Since the input data is large, the computation, which is, in most cases straightforward, is distributed across hundreds or thousands of machines; thus, the application is split into tasks that run in parallel on different machines, tasks that will need to access the data in a highly concurrent manner.
Keywords :
concurrency control; parallel algorithms; concurrent MapReduce applications; data-intensive applications; large-scale distributed storage; Concurrent computing; Data processing; Distributed computing; File servers; File systems; High performance computing; Large-scale systems; Libraries; Throughput; Web and internet services;
Conference_Titel :
Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW), 2010 IEEE International Symposium on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-6533-0
DOI :
10.1109/IPDPSW.2010.5470806